Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 139 742 220 157 986 826 132 934 512 561 902 577 953 611 292 565 97 558 22 61
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] 97 132 220 139 22 61 934 826 512 577 565 157 902 611 NA NA 558 NA 742 986 953 292 561
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 5 1 1 4 1 1 4 3 5 4
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w" "x" "y" "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y" "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "c" "r" "t" "o" "q" "L" "K" "Y" "W" "V"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
[1] 5 8 11 13
which( manyNumbersWithNA > 900 )
[1] 7 13 20 21
which( is.na( manyNumbersWithNA ) )
[1] 15 16 18
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
[1] 986 934 902 953
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
[1] 986 934 902 953
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
[1] 986 934 902 953
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "L" "K" "Y" "W" "V"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "c" "r" "t" "o" "q"
manyNumbers %in% 300:600
[1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE FALSE FALSE FALSE TRUE FALSE TRUE
[19] FALSE FALSE
which( manyNumbers %in% 300:600 )
[1] 9 10 12 16 18
sum( manyNumbers %in% 300:600 )
[1] 5
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] "small" "small" "small" "small" "small" "small" "large" "large" "large" "large" "large" "small" "large" "large"
[15] NA NA "large" NA "large" "large" "large" "small" "large"
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "small" "small" "small" "small" "small" "small" "large" "large" "large" "large" "large"
[12] "small" "large" "large" "UNKNOWN" "UNKNOWN" "large" "UNKNOWN" "large" "large" "large" "small"
[23] "large"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] 0 0 0 0 0 0 934 826 512 577 565 0 902 611 NA NA 558 NA 742 986 953 0 561
unique( duplicatedNumbers )
[1] 5 1 4 3
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 5 1 4 3
duplicated( duplicatedNumbers )
[1] FALSE FALSE TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE
which.max( manyNumbersWithNA )
[1] 20
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 986
which.min( manyNumbersWithNA )
[1] 5
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 22
range( manyNumbersWithNA, na.rm = TRUE )
[1] 22 986
manyNumbersWithNA
[1] 97 132 220 139 22 61 934 826 512 577 565 157 902 611 NA NA 558 NA 742 986 953 292 561
sort( manyNumbersWithNA )
[1] 22 61 97 132 139 157 220 292 512 558 561 565 577 611 742 826 902 934 953 986
sort( manyNumbersWithNA, na.last = TRUE )
[1] 22 61 97 132 139 157 220 292 512 558 561 565 577 611 742 826 902 934 953 986 NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 986 953 934 902 826 742 611 577 565 561 558 512 292 220 157 139 132 97 61 22 NA NA NA
manyNumbersWithNA[1:5]
[1] 97 132 220 139 22
order( manyNumbersWithNA[1:5] )
[1] 5 1 2 4 3
rank( manyNumbersWithNA[1:5] )
[1] 2 3 5 4 1
sort( mixedLetters )
[1] "c" "K" "L" "o" "q" "r" "t" "V" "W" "Y"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 2.0 4.0 5.0 9.0 9.0 2.0 6.5 9.0 2.0 6.5
rank( manyDuplicates, ties.method = "min" )
[1] 1 4 5 8 8 1 6 8 1 6
rank( manyDuplicates, ties.method = "random" )
[1] 3 4 5 9 8 1 7 10 2 6
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.00000000 -0.50000000 0.00000000 0.50000000 1.00000000 -0.01366137 -1.60493282 -0.51333306 -0.11556340
[10] -0.23433664 1.03609279 -0.20477216 0.26285217 0.14166919 -1.70513654
round( v, 0 )
[1] -1 0 0 0 1 0 -2 -1 0 0 1 0 0 0 -2
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 0.0 -1.6 -0.5 -0.1 -0.2 1.0 -0.2 0.3 0.1 -1.7
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 -0.01 -1.60 -0.51 -0.12 -0.23 1.04 -0.20 0.26 0.14 -1.71
floor( v )
[1] -1 -1 0 0 1 -1 -2 -1 -1 -1 1 -1 0 0 -2
ceiling( v )
[1] -1 0 0 1 1 0 -1 0 0 0 2 0 1 1 -1
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 × 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
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